scanLIBRARY
An alternative approach to kinase drug discovery
Red circles (above) represent kinases currently available in the KINOMEscan panel.
The advent of high-throughput kinome-wide compound library profiling has resulted in an alternative and highly parallel kinase inhibitor discovery strategy. In contrast to the traditional drug discovery model where a target is nominated on the basis of biology and screened against a compound library for putative hits in a single-target high-throughput (HTS) screening campaign, KINOME
scan affords researchers the ability to simultaneously screen multiple biological targets of interest, which are also accessible with existing chemical assets.
This strategy harnesses both chemistry and biology data to inform program decisions and direct investments into discovery programs with the best chance of success. By making decisions based on both biological and chemical considerations, time to clinical candidate can be significantly reduced in contrast to the traditional paradigm of pursuing individual targets through HTS screening campaigns. s
canLIBRARY allows for the identification of potent and selective compounds and these high quality lead like compounds can be used to initiate lead optimization programs.
Additionally, a comprehensively annotated kinase-preferred compound collection enables alternative targets of interest to be rapidly pursued should a chemical series display a preference towards them. From a broader perspective, library profiling deepens the knowledgebase regarding chemical SAR and optimization of selectivity/potency. Similarly, mining data for off-target liabilities is integrated with safety information to refine ideal selectivity profiles for clinical candidates (or characterize and manage expected toxicities). There are also indirect benefits to library screening. For instance, a fully profiled library has a defined ‘footprint’ within the kinome. Knowledge of which targets cannot be accessed with the current chemistry reduces the likelihood of pursuing programs ill-suited to achieve the clinical candidate profile. Likewise, compounds may display an array of selectivity patterns that may not only reveal new clinical applications but may also serve as ‘tool’ compounds for investigating
in vitro studies in cells.
As development of kinase inhibitors continues to expand to therapeutic areas beyond oncology, safety and selectivity data will become even more vital. Kinome-wide profiling capitalizes on kinase chemistry by revealing applications across therapeutic areas. Taken to a library profiling scale, this strategy quickly maximizes the investment in a chemical library bringing considerable efficiencies to the competitive arena of kinase drug development.
Benefits
- Screen compound libraries against any KINOMEscan assay panel or single target in our portfolio
- Reveal opportunities and leverage the value inherent in your kinase-focused compound collections
- Make decisions on programs most likely to succeed with existing chemistry
- Reduce time to clinical candidate and with high quality starting points
- Rapidly respond to novel biological targets
High Quality Starting Points From Library Profiling
In contrast to the traditional and largely linear kinase inhibitor discovery model in which one kinase target is assessed at a time, KINOMEscan affords the unprecedented ability to comprehensively annotate entire compound collections against large number of kinases. This highly parallel approach enables organizations to identify multiple targets of interest, defined by target biology, for which high quality lead like compounds exist and to focus resources on those programs most likely to succeed.
Compound Library Annotation Reveals Potential Lead Compounds For Multiple Targets
Identifying the Best Opportunities:
Interrogate Multiple Targets in Parallel
Compound library analysis using selectivity and potency, sorted by kinase target. Data reveals that not all kinase targets are equally accessible with existing chemistry assests, while some kinases can be accessed with hightly selective and potent compounds [click to enlarge].
Annotating Compound Libraries:
High-throughput Kinase Profiling
Top: Heatmap visualization of a compound library (n > 3000, four chemical series) screened against 227 kinases, where green denotes binding interactions. The data demonstrate a pattern between chemical series and kinase selectivity. Lower left: Kinases rank-ordered according to the fraction of compounds they interact with. Lower right: Comparision of selectivity trends for each chemical series. Data courtesy Goldstein et al., Nature Reviews (2008) [click to enlarge].